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Functional Connectivity Based Classification of ADHD Using Different Atlases

Functional Connectivity Based Classification of ADHD Using D...

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Sartaj Ahmed Salman Zhichao Lian Marva Saleem Yuduo Zhang School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (数字)9781728170862

ISBN: (纸本)9781728170879

These days, computational diagnosis strategies of neuropsychiatric disorders are gaining attention day by day. It's critical to determine the brain's functional connectivity based on Functional-Magnetic-Resonance-Imaging(fMRI) to diagnose the disorder. It's known as a chronic disease, and millions of children amass the symptoms of this disease, so there is much vacuum for the researcher to formulate a model to improve the accuracy to diagnose ADHD accurately. In this paper, we consider the functional connectivity of a brain extracted using various time templates/Atlases. Local-Binary Encoding-Method (LBEM) algorithm is utilized for feature extraction, while Hierarchical- Extreme-Learning-Machine (HELM) is used to classify the extracted features. To validate our approach, fMRI data of 143 normal and 100 ADHD affected children is used for experimental purpose. Our experimental results are based on comparing various Atlases given as CC400, CC200, and AAL. Our model achieves high performance with CC400 as compared to other Atlases.

关键词： Technological innovation Functional magnetic resonance imaging Feature extraction Brain modeling Classification algorithms informatics Diseases

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Noninvasive Cardiac Output Monitoring System Based on Photoplethysmography

Noninvasive Cardiac Output Monitoring System Based on Photop...

引用

2014 ieee international conference on progress in informatics and computing

作者： Can Wang Chao Huang Shuming Ye Key lab of Biomedical Engineering of Ministry of Education Zhejiang University College of Biomedical Engineering& Instrument Science Zhejiang University Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal

Cardiac output(CO) is the key indicator of the state of cardiac function. Torealize noninvasive, continuous, portable reproducible cardiac output monitoring, we design a cardiac output monitoring system based on photoplethysmography(PPG)which is stable, non-invasive and convenient tocollect. Kcalibration algorithm is used in the software part of this system The main idea of K-calibration algorithm is tocalibrate the constant K value on the basis of the relationship between the stroke volume(SV) and PPG from invasive SV, then combine the K value and the noninvasive PPG tocalculate the SV, and calculate CO from SV. We collect the invasive SV by FloT rac / Vigileomonitor, and at the same time collect the PPG signals and some other parameters, then combine the calibrated K value and PPG tocalculate SV. After making a correlation analysis with the calculated SV and the invasive SV, the result shows that they have a good correlation with each other. Making a comparison between the continuous CO collected by our designed monitoring system in real time and the invasive CO collected by the FloT rac Vigileomonitoring system will be our follow-up job. And the achievement can be used in mobile or wearable instrument.

关键词： cardiac output PPG noninvasive K-calibration algorithm software system

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Plant CAD:an Integrated Graphic Toolkit for Modelling and Analyzing Plant Structure

Plant CAD:an Integrated Graphic Toolkit for Modelling and An...

引用

2014 ieee international conference on progress in informatics and computing

作者： Shenglian Lu Xinyu Guo Weiliang Wen Boxiang Xiao Chuanyu Wang Jianjun Du Chunjiang Zhao Beijing Research Center for Information Technology in Agriculture

In this paper, we present PlantC AD, a graphic toolkit for the creation, simulation and analysis of 3D virtual plants. This C++-based geometric toolkit allows easy generation of plant organs including leaves, fruits, branches, petioles and even nonbotanical things which makes it a powerful userinteractive platform for plant modeling in various biological application. Based on the basic geometric components dedicated todifferent organs, PlantC AD provides several methods tocreate plant structure from either real measured data or procedural models. Realistic appearance of the generated 3D plants is improved by using texture mapping and including hairs that cover many plant organs. Several examples from different modelling applications illustrate how Plant CAD can be used toconstruct, analyse or manipulate geometric models at different scales ranging from organs toplant communities.

关键词： modelling plant structure 3D reconstruction visualization realistic rendering

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Evaluation of T Wave Altemans Detectors Based on a Simulation Study

Evaluation of T Wave Altemans Detectors Based on a Simulatio...

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The 2010 ieee international conference on progress in informatics and computing

作者： Xiankui Wan and Du Xu Information Engineering College Guangdong University of Technology Guangzhou,China Fulan Xie Liwan Hospital Guangzhou Media University Guangzhou,China

a simulation study of T wave alternans(TWA) is proposed in order to evaluate the performance of typically used TWA detectors,as well as to quantify the performance characteristics in terms of sensitivity,positive predictivity and beat-to-beat amplitude estimation *** signals are simulated repeating a single beat,and adding mixed noise from 4 different noise sources at different *** episodes with different amplitudes and waveforms were added to the signals. We can conclude from this study that the correlation-based detector obtained much lower detection rates than the other detectors,especially in sensitivity for low amplitude *** amplitude accuracy in the detected episodes was also found to be the worst with correlation-based *** other detectors have shown a similar ***,the complex demodulation detector needs a much higher computational *** general,alternans are detected with rates near 100%for SNR greater than 10 dB for physiological noise sources.

关键词： T-wave alternans evaluation spectral method complex demodulation correlation method modified moving average method

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Aerodynamic optimization designing of Airfoil based on Isight

Aerodynamic optimization designing of Airfoil based on Isigh...

引用

The 2010 ieee international conference on progress in informatics and computing

作者： Wei Wang,Rong Mo,Zhiyong Chang,Huibin Sun Ministry of Education Key Lab of Contemporary Design & Integrated Manu.Tech. Northwestern Polytechnical Univ. Xi'an,China

In order to improving the designing efficiency and achieving automation of airfoil optimization designing,A method which combined the airfoil parametric modeling software、the CFD software with Isight platform was presented,it was used to optimize the airfoil to ameliorate its aerodynamic performance. During the process of optimization designing,first,we adopted the design of experiment(DOE) method to search the designing space,achieved the optimal initialization ***,we adopted Non-dominated Sorting Genetic Algorithm(NSGA-Ⅱ) to optimize the airfoil,got the optimal airfoil aerodynamic solution. The optimized solution proved that the aerodynamic performance of the airfoil has been significantly improved,which shows the optimization designing method was reasonable and feasible.

关键词： Isight Design of Experiment(DOE) Non-dominated Sorting Genetic Algorithm(NSGA-II) Aerodynamic Optimization Designing of Airfoil

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A Preliminary Experimental Study on Optimal Feature Selection for Product Derivation Using Knapsack Approximation

A Preliminary Experimental Study on Optimal Feature Selectio...

引用

The 2010 ieee international conference on progress in informatics and computing

作者： Runyu Shi,Jianmei Guo,and Yinglin Wang Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240,China

Software product lines(SPLs) technology produce software by integrating reusable software components based on customer *** researchers pay great attention to feature modeling technology that can represent SPLs' production requirements and functionalities.A key challenge is selecting valid and optimal feature combinations from the feature model to satisfy various requirements of customers and vendors, including various value and cost *** paper experimentally studies a knapsack approximation algorithm of feature selection for automated product derivation in *** approach generates an approximation solution by a modified Filtered Cartesian Flattening algorithm and obtains the optimal solution with a greed *** performed experiments on randomly generated feature models with different characteristics. Experiments show that our approach can select highly optimal feature combinations effectively.

关键词： software product lines product derivation feature models approximation algorithm

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A Finite-State Automata based Negation Detection Algorithm for Chinese Clinical Documents

A Finite-State Automata based Negation Detection Algorithm f...

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2014 ieee international conference on progress in informatics and computing

作者： Zheng Jia Haomin Li Meizhi Ju Yinsheng Zhang Zhenzhen Huang Caixia Ge Huilong Duan College of Biomedical Engineering and Instrument Science Zhejiang University School of Medicine Zhejiang University

In this paper we described an algorithm called Neg Detector for locating concerned clinical terms mentioned in electronic narrative text clinical documents and detecting whether the particular terms appeared in different positions are negated or affirmed. The algorithm infers the status of a condition with regard tothe property from simple lexical clues occurring in the context of condition, maybe more than a few words away from the term. Considering the diverse types of negative structures, this paper selects typical, common and recognizable usage patterns of negatives as criteria of judgment. The judging results during one complete process are driven by many different types of symbols, and the response toa particular symbol depends on the sequence of previous judging results. In this situation, the finite-state automata is useful toaddress lots of symbols that trigger one another. When evaluating Neg Detector with testing case history, we measured a recall of 0.9985, a precision of 0.9498 and a fallout of 0.5147.

关键词： Chinese negation detection Finite-State Automata MLP

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Dynamic Windowing Strategies for Concept Drift Type Classification in Data Streams

Dynamic Windowing Strategies for Concept Drift Type Classifi...

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Khanh-Tung Nguyen Quang-Thuy Ha Xuan-Hieu Phan Electric Power University Hanoi Vietnam University of Engineering and Technology Vietnam National University Hanoi Vietnam

ISBN: (数字)9798350363203

ISBN: (纸本)9798350363210

Detecting and classifying concept drift in data streams is essential for maintaining the accuracy and reliability of machine learning models deployed in dynamic environments. Traditional drift detection methods often apply a single windowing strategy across all drift types, limiting their ability to distinguish between sudden, gradual, incremental drifts. In this paper, we propose a novel approach that leverages tailored windowing strategies to enhance the performance of concept drift classifiers. Specifically, we apply sliding windows for gradual drift, tumbling windows for sudden drift, expanding windows for incremental drift, aligning each strategy with the characteristics of the respective drift type. By generating synthetic data streams using these customized windowing strategies, we train a drift classifier capable of both detecting and accurately classifying different types of drift in real-time data streams. Experimental results show that our approach significantly improves drift detection accuracy and classification performance compared to conventional windowing methods. These findings highlight the potential of tailored pre-training strategies in adaptive systems and offer a pathway for developing more robust and context-aware drift detection solutions.

关键词： Accuracy Limiting Error analysis Concept drift Feature extraction Real-time systems Reliability informatics Streams Synthetic data

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Mask Inpaints Using Downsampled Fast Fourier Convolution

Mask Inpaints Using Downsampled Fast Fourier Convolution

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Xiaoyang Gao Yifan Huang Penghui Gao Yong Zhang Tao Yang School of Information and Intelligence Engineering University of Sanya Hainan China Academician Workstation of Chumming Rong University of Sanya Hainan China

ISBN: (数字)9798350363203

ISBN: (纸本)9798350363210

In recent years, image inpainting has seen significant advancements, with the LaMa model., introduced in 2021, standing out for its improvements in large-area inpainting. Yet, challenges such as inpainting complex geometries, processing high-resolution images swiftly, and achieving realism in filled areas persist. Existing solutions that incorporate diffusion models to enhance realism are hardware-intensive and unsuitable for high-resolution images. We propose a new image inpainting method, Downsampled Fast Fourier Convolution (DFFC), which addresses these challenges. Unlike LaMa's reliance on Fast Fourier Convolution (FFC) for early-stage global context capture without explicit downsampling, DFFC introduces a deep learning-driven downsampling module to reduce computational complexity and improve high-resolution image processing efficiency. This module allows for data volume reduction during processing while preserving global context, comprising: i) deep learning-based image downsampling, ii) an FFC-based inpainting architecture, iii) a high-perceptual-domain loss function, and iv) dynamic large-area mask training. Our method maintains the original model's performance, enhances processing speed, and reduces computational load.

关键词： Training Geometry Convolution Image processing Computational modeling Computer architecture Diffusion models informatics Computational complexity Load modeling

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Cluster Tree Based Hybrid Semantic Similarity Measure for Social Tagging Systems

Cluster Tree Based Hybrid Semantic Similarity Measure for So...

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The 2010 ieee international conference on progress in informatics and computing

作者： Changli Zhang School of Information Engineering Chang'an University Xi'an 710064,China Jinjin Zhang,Maode Yan School of Electronics & Control Engineering Chang'an University Xi'an 710064,China

As the social tagging systems becoming prevalent,it remains a critical question that how to make explicit the semantics for tags to fully facilitate Web2.0 *** paper establishes a cluster tree based semantic similarity measure for social tagging systems,combines it with traditional statistics based measures into a hybrid one,tailors the hybrid measure according to the effectiveness requirement of intelligent search application,and presents a case study using the empirical data retrieved from *** *** to the traditional statistics based measures,our hybrid measure is capable of evaluating similarities between random tags even not co-occurred,can better reflect the structural influence of the network of tag co-occurrence,and is feasible for applications like intelligent search in user-centric Web2.0 environment.

关键词： social tagging systems semantic similarity measure cluster tree folkosonomy small world intelligent search Web2.0

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